SIMD based multicore processor for image and video processing

制度:新 ; 報告番号:甲3602号 ; 学位の種類:博士(工学) ; 授与年月日:2012/3/15 ; 早大学位記番号:新595

Elastic, Interoperable and Container-based Cloud Infrastructures for High Performance Computing

Tesis por compendio[ES] Las aplicaciones científicas implican generalmente una carga computacional variable y no predecible a la que las instituciones deben hacer frente variando dinámicamente la asignación de recursos en función de las distintas necesidades computacionales. Las aplicaciones científicas pueden necesitar grandes requisitos. Por ejemplo, una gran cantidad de recursos computacionales para el procesado de numerosos trabajos independientes (High Throughput Computing o HTC) o recursos de alto rendimiento para la resolución de un problema individual (High Performance Computing o HPC). Los recursos computacionales necesarios en este tipo de aplicaciones suelen acarrear un coste muy alto que puede exceder la disponibilidad de los recursos de la institución o estos pueden no adaptarse correctamente a las necesidades de las aplicaciones científicas, especialmente en el caso de infraestructuras preparadas para la ejecución de aplicaciones de HPC. De hecho, es posible que las diferentes partes de una aplicación necesiten distintos tipos de recursos computacionales. Actualmente las plataformas de servicios en la nube se han convertido en una solución eficiente para satisfacer la demanda de las aplicaciones HTC, ya que proporcionan un abanico de recursos computacionales accesibles bajo demanda. Por esta razón, se ha producido un incremento en la cantidad de clouds híbridos, los cuales son una combinación de infraestructuras alojadas en servicios en la nube y en las propias instituciones (on-premise). Dado que las aplicaciones pueden ser procesadas en distintas infraestructuras, actualmente la portabilidad de las aplicaciones se ha convertido en un aspecto clave. Probablemente, las tecnologías de contenedores son la tecnología más popular para la entrega de aplicaciones gracias a que permiten reproducibilidad, trazabilidad, versionado, aislamiento y portabilidad. El objetivo de la tesis es proporcionar una arquitectura y una serie de servicios para proveer infraestructuras elásticas híbridas de procesamiento que puedan dar respuesta a las diferentes cargas de trabajo. Para ello, se ha considerado la utilización de elasticidad vertical y horizontal desarrollando una prueba de concepto para proporcionar elasticidad vertical y se ha diseñado una arquitectura cloud elástica de procesamiento de Análisis de Datos. Después, se ha trabajo en una arquitectura cloud de recursos heterogéneos de procesamiento de imágenes médicas que proporciona distintas colas de procesamiento para trabajos con diferentes requisitos. Esta arquitectura ha estado enmarcada en una colaboración con la empresa QUIBIM. En la última parte de la tesis, se ha evolucionado esta arquitectura para diseñar e implementar un cloud elástico, multi-site y multi-tenant para el procesamiento de imágenes médicas en el marco del proyecto europeo PRIMAGE. Esta arquitectura utiliza un almacenamiento distribuido integrando servicios externos para la autenticación y la autorización basados en OpenID Connect (OIDC). Para ello, se ha desarrollado la herramienta kube-authorizer que, de manera automatizada y a partir de la información obtenida en el proceso de autenticación, proporciona el control de acceso a los recursos de la infraestructura de procesamiento mediante la creación de las políticas y roles. Finalmente, se ha desarrollado otra herramienta, hpc-connector, que permite la integración de infraestructuras de procesamiento HPC en infraestructuras cloud sin necesitar realizar cambios en la infraestructura HPC ni en la arquitectura cloud. Cabe destacar que, durante la realización de esta tesis, se han utilizado distintas tecnologías de gestión de trabajos y de contenedores de código abierto, se han desarrollado herramientas y componentes de código abierto y se han implementado recetas para la configuración automatizada de las distintas arquitecturas diseñadas desde la perspectiva DevOps.[CA] Les aplicacions científiques impliquen generalment una càrrega computacional variable i no predictible a què les institucions han de fer front variant dinàmicament l'assignació de recursos en funció de les diferents necessitats computacionals. Les aplicacions científiques poden necessitar grans requisits. Per exemple, una gran quantitat de recursos computacionals per al processament de nombrosos treballs independents (High Throughput Computing o HTC) o recursos d'alt rendiment per a la resolució d'un problema individual (High Performance Computing o HPC). Els recursos computacionals necessaris en aquest tipus d'aplicacions solen comportar un cost molt elevat que pot excedir la disponibilitat dels recursos de la institució o aquests poden no adaptar-se correctament a les necessitats de les aplicacions científiques, especialment en el cas d'infraestructures preparades per a l'avaluació d'aplicacions d'HPC. De fet, és possible que les diferents parts d'una aplicació necessiten diferents tipus de recursos computacionals. Actualment les plataformes de servicis al núvol han esdevingut una solució eficient per satisfer la demanda de les aplicacions HTC, ja que proporcionen un ventall de recursos computacionals accessibles a demanda. Per aquest motiu, s'ha produït un increment de la quantitat de clouds híbrids, els quals són una combinació d'infraestructures allotjades a servicis en el núvol i a les mateixes institucions (on-premise). Donat que les aplicacions poden ser processades en diferents infraestructures, actualment la portabilitat de les aplicacions s'ha convertit en un aspecte clau. Probablement, les tecnologies de contenidors són la tecnologia més popular per a l'entrega d'aplicacions gràcies al fet que permeten reproductibilitat, traçabilitat, versionat, aïllament i portabilitat. L'objectiu de la tesi és proporcionar una arquitectura i una sèrie de servicis per proveir infraestructures elàstiques híbrides de processament que puguen donar resposta a les diferents càrregues de treball. Per a això, s'ha considerat la utilització d'elasticitat vertical i horitzontal desenvolupant una prova de concepte per proporcionar elasticitat vertical i s'ha dissenyat una arquitectura cloud elàstica de processament d'Anàlisi de Dades. Després, s'ha treballat en una arquitectura cloud de recursos heterogenis de processament d'imatges mèdiques que proporciona distintes cues de processament per a treballs amb diferents requisits. Aquesta arquitectura ha estat emmarcada en una col·laboració amb l'empresa QUIBIM. En l'última part de la tesi, s'ha evolucionat aquesta arquitectura per dissenyar i implementar un cloud elàstic, multi-site i multi-tenant per al processament d'imatges mèdiques en el marc del projecte europeu PRIMAGE. Aquesta arquitectura utilitza un emmagatzemament integrant servicis externs per a l'autenticació i autorització basats en OpenID Connect (OIDC). Per a això, s'ha desenvolupat la ferramenta kube-authorizer que, de manera automatitzada i a partir de la informació obtinguda en el procés d'autenticació, proporciona el control d'accés als recursos de la infraestructura de processament mitjançant la creació de les polítiques i rols. Finalment, s'ha desenvolupat una altra ferramenta, hpc-connector, que permet la integració d'infraestructures de processament HPC en infraestructures cloud sense necessitat de realitzar canvis en la infraestructura HPC ni en l'arquitectura cloud. Es pot destacar que, durant la realització d'aquesta tesi, s'han utilitzat diferents tecnologies de gestió de treballs i de contenidors de codi obert, s'han desenvolupat ferramentes i components de codi obert, i s'han implementat receptes per a la configuració automatitzada de les distintes arquitectures dissenyades des de la perspectiva DevOps.[EN] Scientific applications generally imply a variable and an unpredictable computational workload that institutions must address by dynamically adjusting the allocation of resources to their different computational needs. Scientific applications could require a high capacity, e.g. the concurrent usage of computational resources for processing several independent jobs (High Throughput Computing or HTC) or a high capability by means of using high-performance resources for solving complex problems (High Performance Computing or HPC). The computational resources required in this type of applications usually have a very high cost that may exceed the availability of the institution's resources or they are may not be successfully adapted to the scientific applications, especially in the case of infrastructures prepared for the execution of HPC applications. Indeed, it is possible that the different parts that compose an application require different type of computational resources. Nowadays, cloud service platforms have become an efficient solution to meet the need of HTC applications as they provide a wide range of computing resources accessible on demand. For this reason, the number of hybrid computational infrastructures has increased during the last years. The hybrid computation infrastructures are the combination of infrastructures hosted in cloud platforms and the computation resources hosted in the institutions, which are named on-premise infrastructures. As scientific applications can be processed on different infrastructures, the application delivery has become a key issue. Nowadays, containers are probably the most popular technology for application delivery as they ease reproducibility, traceability, versioning, isolation, and portability. The main objective of this thesis is to provide an architecture and a set of services to build up hybrid processing infrastructures that fit the need of different workloads. Hence, the thesis considered aspects such as elasticity and federation. The use of vertical and horizontal elasticity by developing a proof of concept to provide vertical elasticity on top of an elastic cloud architecture for data analytics. Afterwards, an elastic cloud architecture comprising heterogeneous computational resources has been implemented for medical imaging processing using multiple processing queues for jobs with different requirements. The development of this architecture has been framed in a collaboration with a company called QUIBIM. In the last part of the thesis, the previous work has been evolved to design and implement an elastic, multi-site and multi-tenant cloud architecture for medical image processing has been designed in the framework of a European project PRIMAGE. This architecture uses a storage integrating external services for the authentication and authorization based on OpenID Connect (OIDC). The tool kube-authorizer has been developed to provide access control to the resources of the processing infrastructure in an automatic way from the information obtained in the authentication process, by creating policies and roles. Finally, another tool, hpc-connector, has been developed to enable the integration of HPC processing infrastructures into cloud infrastructures without requiring modifications in both infrastructures, cloud and HPC. It should be noted that, during the realization of this thesis, different contributions to open source container and job management technologies have been performed by developing open source tools and components and configuration recipes for the automated configuration of the different architectures designed from the DevOps perspective. The results obtained support the feasibility of the vertical elasticity combined with the horizontal elasticity to implement QoS policies based on a deadline, as well as the feasibility of the federated authentication model to combine public and on-premise clouds.López Huguet, S. (2021). Elastic, Interoperable and Container-based Cloud Infrastructures for High Performance Computing [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/172327TESISCompendi

Ultra low power cooperative branch prediction

Branch Prediction is a key task in the operation of a high performance processor. An inaccurate branch predictor results in increased program run-time and a rise in energy consumption. The drive towards processors with limited die-space and tighter energy requirements will continue to intensify over the coming years, as will the shift towards increasingly multicore processors. Both trends make it increasingly important and increasingly difficult to find effective and efficient branch predictor designs. This thesis presents savings in energy and die-space through the use of more efficient cooperative branch predictors achieved through novel branch prediction designs. The first contribution is a new take on the problem of a hybrid dynamic-static branch predictor allocating branches to be predicted by one of its sub-predictors. A new bias parameter is introduced as a mechanism for trading off a small amount of performance for savings in die-space and energy. This is achieved by predicting more branches with the static predictor, ensuring that only the branches that will most benefit from the dynamic predictor’s resources are predicted dynamically. This reduces pressure on the dynamic predictor’s resources allowing for a smaller predictor to achieve very high accuracy. An improvement in run-time of 7-8% over the baseline BTFN predictor is observed at a cost of a branch predictor bits budget of much less than 1KB. Next, a novel approach to branch prediction for multicore data-parallel applications is presented. The Peloton branch prediction scheme uses a pack of cyclists as an illustration of how a group of processors running similar tasks can share branch predictions to improve accuracy and reduce runtime. The results show that sharing updates for conditional branches across the existing interconnect for I-cache and D-cache updates results in a reduction of mispredictions of up to 25% and a reduction in run-time of up to 6%. McPAT is used to present an energy model that suggests the savings are achieved at little to no increase in energy required. The technique is then extended to architectures where the size of the branch predictors may differ between cores. The results show that such heterogeneity can dramatically reduce the die-space required for an accurate branch predictor while having little impact on performance and up to 9% energy savings. The approach can be combined with the Peloton branch prediction scheme for reduction in branch mispredictions of up to 5%

Rotary Wing Aerodynamics

This book contains state-of-the-art experimental and numerical studies showing the most recent advancements in the field of rotary wing aerodynamics and aeroelasticity, with particular application to the rotorcraft and wind energy research fields

Enhancing the efficiency and practicality of software transactional memory on massively multithreaded systems

Chip Multithreading (CMT) processors promise to deliver higher performance by running more than one stream of instructions in parallel. To exploit CMT's capabilities, programmers have to parallelize their applications, which is not a trivial task. Transactional Memory (TM) is one of parallel programming models that aims at simplifying synchronization by raising the level of abstraction between semantic atomicity and the means by which that atomicity is achieved. TM is a promising programming model but there are still important challenges that must be addressed to make it more practical and efficient in mainstream parallel programming. The first challenge addressed in this dissertation is that of making the evaluation of TM proposals more solid with realistic TM benchmarks and being able to run the same benchmarks on different STM systems. We first introduce a benchmark suite, RMS-TM, a comprehensive benchmark suite to evaluate HTMs and STMs. RMS-TM consists of seven applications from the Recognition, Mining and Synthesis (RMS) domain that are representative of future workloads. RMS-TM features current TM research issues such as nesting and I/O inside transactions, while also providing various TM characteristics. Most STM systems are implemented as user-level libraries: the programmer is expected to manually instrument not only transaction boundaries, but also individual loads and stores within transactions. This library-based approach is increasingly tedious and error prone and also makes it difficult to make reliable performance comparisons. To enable an "apples-to-apples" performance comparison, we then develop a software layer that allows researchers to test the same applications with interchangeable STM back ends. The second challenge addressed is that of enhancing performance and scalability of TM applications running on aggressive multi-core/multi-threaded processors. Performance and scalability of current TM designs, in particular STM desings, do not always meet the programmer's expectation, especially at scale. To overcome this limitation, we propose a new STM design, STM2, based on an assisted execution model in which time-consuming TM operations are offloaded to auxiliary threads while application threads optimistically perform computation. Surprisingly, our results show that STM2 provides, on average, speedups between 1.8x and 5.2x over state-of-the-art STM systems. On the other hand, we notice that assisted-execution systems may show low processor utilization. To alleviate this problem and to increase the efficiency of STM2, we enriched STM2 with a runtime mechanism that automatically and adaptively detects application and auxiliary threads' computing demands and dynamically partition hardware resources between the pair through the hardware thread prioritization mechanism implemented in POWER machines. The third challenge is to define a notion of what it means for a TM program to be correctly synchronized. The current definition of transactional data race requires all transactions to be totally ordered "as if'' serialized by a global lock, which limits the scalability of TM designs. To remove this constraint, we first propose to relax the current definition of transactional data race to allow a higher level of concurrency. Based on this definition we propose the first practical race detection algorithm for C/C++ applications (TRADE) and implement the corresponding race detection tool. Then, we introduce a new definition of transactional data race that is more intuitive, transparent to the underlying TM implementation, can be used for a broad set of C/C++ TM programs. Based on this new definition, we proposed T-Rex, an efficient and scalable race detection tool for C/C++ TM applications. Using TRADE and T-Rex, we have discovered subtle transactional data races in widely-used STAMP applications which have not been reported in the past

Non-oscillatory forward-in-time method for incompressible flows

This research extends the capabilities of Non-oscillatory Forward-in-Time (NFT) solvers operating on unstructured meshes to allow for accurate simulation of incompressible turbulent flows. This is achieved by the development of Large Eddy Simulation (LES) and Detached Eddy Simulation (DES) turbulent flow methodologies and the development of parallel option of the flow solver. The effective use of LES and DES requires a development of a subgrid-scale model. Several subgrid-scale models are implemented and studied, and their efficacy is assessed. The NFT solvers employed in this work are based on the Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) that facilitates novel implicit Large Eddy Simulation (ILES) approach to treating turbulence. The flexibility and robustness of the new NFT MPDATA solver are studied and successfully validated using well established benchmarks and concentrate on a flow past a sphere. The flow statistics from the solutions are compared against the existing experimental and numerical data and fully confirm the validity of the approach. The parallel implementation of the flow solver is also documented and verified showing a substantial speedup of computations. The proposed method lays foundations for further studies and developments, especially for exploring the potential of MPDATA in the context of ILES and associated treatments of boundary conditions at solid boundaries

Proyecto Docente e Investigador, Trabajo Original de Investigación y Presentación de la Defensa, preparado por Germán Moltó para concursar a la plaza de Catedrático de Universidad, concurso 082/22, plaza 6708, área de Ciencia de la Computación e Inteligencia Artificial

Este documento contiene el proyecto docente e investigador del candidato Germán Moltó Martínez presentado como requisito para el concurso de acceso a plazas de Cuerpos Docentes Universitarios. Concretamente, el documento se centra en el concurso para la plaza 6708 de Catedrático de Universidad en el área de Ciencia de la Computación en el Departamento de Sistemas Informáticos y Computación de la Universitat Politécnica de València. La plaza está adscrita a la Escola Técnica Superior d'Enginyeria Informàtica y tiene como perfil las asignaturas "Infraestructuras de Cloud Público" y "Estructuras de Datos y Algoritmos".También se incluye el Historial Académico, Docente e Investigador, así como la presentación usada durante la defensa.Germán Moltó Martínez (2022). Proyecto Docente e Investigador, Trabajo Original de Investigación y Presentación de la Defensa, preparado por Germán Moltó para concursar a la plaza de Catedrático de Universidad, concurso 082/22, plaza 6708, área de Ciencia de la Computación e Inteligencia Artificial. http://hdl.handle.net/10251/18903

Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version

Multibody dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: Formulations and Numerical Methods, Efficient Methods and Real-Time Applications, Flexible Multibody Dynamics, Contact Dynamics and Constraints, Multiphysics and Coupled Problems, Control and Optimization, Software Development and Computer Technology, Aerospace and Maritime Applications, Biomechanics, Railroad Vehicle Dynamics, Road Vehicle Dynamics, Robotics, Benchmark Problems. The conference is organized by the Department of Mechanical Engineering of the Universitat Politècnica de Catalunya (UPC) in Barcelona. The organizers would like to thank the authors for submitting their contributions, the keynote lecturers for accepting the invitation and for the quality of their talks, the awards and scientific committees for their support to the organization of the conference, and finally the topic organizers for reviewing all extended abstracts and selecting the awards nominees.Postprint (published version